Zero-one Goal Programming Model Research Articles

A hybrid approach to supporting physical-change-based renewal projects selection decisions in high-density city: a case study of Chongqing

Purpose The aims of this paper is to establish an appropriate physical-change-based renewal (PCBR) projects selection mechanism capable of selecting the combination of the PCBR projects that can make up an integrated urban renewal program in high-density cities.Design/methodology/approach The research design follows a sequential integrated methodology that combines the calculation algorithms of Fuzzy Analytic Network Process (Fuzzy-ANP) with Zero-One Goal Programming (ZOGP) to support decisions for the selection of PCBR projects. In the first phase, general criteria for assessing the sustainability performance of PCBR projects were collected from relevant literature. In the second phase, the Fuzzy-ANP was used to identify the priority weights of the candidate projects through clarifying the interdependent degree between the criteria and candidate projects. Finally, ZOGP method was selected as a predetermined number of PCBR projects among candidate projects.Findings The feasibility and effectiveness of this hybrid approach is then verified in a case study of Yuzhong District, Chongqing in China. The results of this study indicate that the integrated method is capable of directing the decision maker toward the best compromising solution of PCBR program that can achieve the maximization of sustainable benefits and allocate limited resources most efficiently.Originality/value The novelty of this paper consists in combining the algorithms of the Fuzzy-ANP method with those of the ZOGP model that serves as an effective analysis tool to address practical decision problems. This is the first hybrid algorithms to make PCBR projects selection decision that reach the maximization of the sustainable benefits, both in economic and socio-environmental terms.

An integrated approach of fuzzy risk assessment model and data envelopment analysis for route selection in multimodal transportation networks

The main objective of this study is to first propose a novel integrated framework of fuzzy risk assessment model (FRAM), data envelopment analysis (DEA), and multiple criteria decision-making (MCDM) approaches for route selection in multimodal transportation networks. In the FRAM phase, the magnitude calculation of risks was operated by decision makers, who can provide their opinions on the probability of occurrence and severity of consequences through linguistic variables and triangular fuzzy numbers for risk likelihood and severity scales. The Mamdani fuzzy rule-based inference system including the rule’s firing strengths is established to convert the membership degrees for each term of aggregated likelihood and severity scales into those for each term of the risk magnitude scale. In the DEA phase, precise and crisp risk magnitudes are characterized by a new defuzzifier based on the DEA algorithm, which is applied instead of classical defuzzification methods. The three decision criteria of transportation cost, transportation time, and overall risk magnitude are weighted by a fuzzy analytic hierarchy process and then investigated based on the consensus of decision makers’ needs by a zero-one goal programming model, which is used to select the most appropriate multimodal route. Finally, the integrated approach is tested to reveal its capability and aptness using a real-world multimodal freight transportation route selection between Thailand and Cambodia. The proposed framework contributes to an easy-to-apply technique for risk predictability in multimodal transportation networks and provides powerful decision-making for the effective selection of the most appropriate alternative under the fuzzy context.

A zero-one goal programming model to use financial resources

Supplier selection is a multi-criteria decision-making process. Suppliers should decide which resources to invest in with limited resources. Goal programming can support this decision-making process. Thus, this study used a case study to show this process by applying goal programming.

A hybrid quality function deployment and fuzzy decision-making methodology for the optimal selection of third-party logistics service providers

As the third-party logistics service provider (3PL) industry continues to grow, the optimal selection of a 3PL has become one of the most challenging tasks due to a larger pool of qualified 3PLs and their variety of service offerings. This challenge calls for a systematic decision-aid tool which can not only handle the increased complexity of 3PL selection problems, but also reflect the realities of logistics outsourcing issues that cannot be easily quantified. The paper aims to propose a hybrid quality function deployment (QFD) and fuzzy decision-making methodology for solving 3PL evaluation/selection problem. First, QFD is utilised to structure specific customer service needs and match those needs to the characteristics of 3PL candidates. Fuzzy linear regression is then employed to determine a functional relationship between the 3PL user's logistics service needs and the 3PL characteristics. Finally, a zero-one goal programming model is used to select the most desirable 3PL under multiple decision criteria.

Analytic network process-based model for selecting an optimal product design solution with zero–one goal programming

Successive new product development is essential to ensure continual growth of a company. However, any wrong decision-making may cause a catastrophe before the company could benefit from it. Consequently, selecting an appropriate design solution by the product development team or upper management that meets the broad interest of a company has become an important part of new product development. In this paper, we propose a systematic methodology that integrates analytic network process (ANP) and zero–one goal programming (ZOGP) in order to select an optimal product design solution. Before introducing the ANP and ZOGP methods, the fuzzy Delphi method is first adopted to identify the essential factors that have influences on the selection results. Followed by the ANP method, which is used to determine the weights of the proposed product design alternatives, a mathematical ZOGP model is built to incorporate multiple objectives in order to reach the optimal solution. Finally, the MP3 player product design project is used as an empirical example to illustrate the overall decision procedure and to examine the effectiveness of our proposed new model.

Designing a quality control system in a service organization: A goal programming case study

Not all service organizations have established formal quality control (QC) procedures. A review of the literature helps develop a list of indicants defining the quality construct. These indicants are, in turn, incorporated into a goal programming model for the design of a QC system in service organizations. A zero-one goal programming model is developed to help select the “best” set of quality control instruments for customer data collection purposes. A real world case study illustrates the application of this model.

A multi-objective constrained resource information system project selection method

This paper demonstrates the application of a zero-one goal programming model as a decision method for selecting information system (IS) projects. This paper illustrates the importance of using multi-objective, constrained resource modeling in IS project selection decision making. A comparative example demonstrating the consequences for a regional utility company that used the more common ranking selection methods is presented as a case study. The results changed the utility company's selection process by showing how IS management resources can be saved and how the typical IS project selection criteria can be easily incorporated into a model for improved decision making.

Multinational acquisition analysis: A zero-one goal programming model

This paper presents a multi-objective model using critical success factors (CSF) as a basis for international business expansion analysis. The paper describes a process by which international business expansion analysis (i.e., the act of selecting a corporation for acquisition or merger in the multinational environment), can be performed requiring less management time and providing additional decision making information. A zero-one goal programming (ZOGP) model is developed and applied using a case study in international business expansion. The results of the application demonstrate the ease of use of the ZOGP model and its informational efficiency.

Transmission line route selection by goal programming

A two-stage solution for transmission line route selection is presented. The generalized double-sweep method has been used to select the K least costly routes. The selected routes are subjected to social and environmental constraints (SEC). The SEC problem is formulated as a zero-one goal-programming model and solved by the implicit enumeration method. The two-stage solution algorithm has been applied to two problems. The results indicate the suitability of the method for route selection provided that acceptable SEC criteria can be found. The results also indicate the viability of the goal-programming technique for choosing power network interconnection concepts.

A goal approach to assembly line balancing

A zero-one goal programming model for the assembly line balancing problem is developed. The goal model provides increased flexibility in constructing line balances by simultaneously considering varying operational requirements, such as zoning, sequencing, idle time, cycle time and costs. A sensitivity analysis of an example model highlights the usefulness of the approach in the planning stages of a line balance development.

A disaggregate zero-one goal programming model for the flexible staff scheduling problem

This paper proposes an interactive zero-one pre-emptive goal programming model for real-world workforce scheduling procedures. To be useful in practice, the proposed model takes into account the disaggregate and non-cyclical nature of staff scheduling decisions, which has been largely ignored in the existing literature. Hence, the model is partitioned into a number of smaller submodels based on three phases and then formulated for solving each separate and disaggregate level workforce scheduling problem. In addition, to make the model computationally tractable for large-scale workforce scheduling problems, we propose and describe two efficient, and easy-to-use heuristics which even non-technical schedulers can implement. Finally, to demonstrate the practicality of the proposed model and its solution schemes, we present and discuss the application of the model to a real-world library staff scheduling decision.

A Nonlinear Zero-One Combinatorial, Goal-Programming Model and Constructive Algorithm for Solving Multiobjective Assignment Problems

This paper describes a technique for assigning orders against specific reels of inventoried cable to ensure a high level of customer service, efficient labor utilization, highly usable cable lengths in inventory, and minimal scrap. Some orders are interrelated and thus linked, requiring that the assignment of each order be contingent upon the assignment of all linked orders. Due to this contingency, penalties associated with certain assignments, and selection allowances, the problem is quite complex. Our method of solution is formulated as a preemptive, multipriority, zero-one goal programming model used in a constructive initial placement algorithm. The model is primarily linear, but it also contains some nonlinear terms. The goal programming model and initial constructive algorithm run weekly in a production environment that handles up to 100 orders and 150 reels per problem.

A zero-one goal programming model for capital budgeting in a property and liability insurance company

This paper presents a zero-one goal programming model for capital budgeting in a property and liability insurance company. The model structure allows for the inclusion of multiple goals, indivisible projects and a multiple period planning horizon. The model offers an advantage of being closer to reality than many previous models and, at the same time, is easy for decision makers to understand and use. Model solutions and sensitivity analyses are presented.